面向地震设防风险的未来中国城乡人口情景及暴露特征

doi:10.12006/j.issn.1673-1719.2021.271

气候变化研究进展 ›› 2022, Vol. 18 ›› Issue (6): 707-719.doi: 10.12006/j.issn.1673-1719.2021.271

面向地震设防风险的未来中国城乡人口情景及暴露特征

张化¹^,⁴(), 李汶莉²^,³, 李雪敏²^,³, 董琳²^,³, 杨有田²^,³, 张国明¹^,⁴, 许映军¹^,⁴

1 北京师范大学国家安全与应急管理学院，北京 100875
2 北京师范大学地理科学学部，北京 100875
3 北京师范大学民政部教育部减灾与应急管理研究院，北京 100875
4 北京师范大学环境演变与自然灾害教育部重点实验室，北京 100875

收稿日期:2021-12-02 修回日期:2022-03-07 出版日期:2022-11-30 发布日期:2022-10-27
作者简介:张化，男，高级工程师，zhanghua2011@bnu.edu.cn
基金资助:
国家重点研究开发项目“海岸带和沿海地区全球变化综合风险研究”(2017YFA0604903);国家重点研究开发项目“海岸带和沿海地区全球变化综合风险研究”(2017YFA0604904)

Analysis of urban and rural population scenarios and exposure characteristics in China in the future for the prevention of earthquake risk

ZHANG Hua¹^,⁴(), LI Wen-Li²^,³, LI Xue-Min²^,³, DONG Lin²^,³, YANG You-Tian²^,³, ZHANG Guo-Ming¹^,⁴, XU Ying-Jun¹^,⁴

1 School of National Safety and Emergency Management, Beijing Normal University, Beijing 100875, China
2 Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
3 Academy of Disaster Reduction and Emergency Management Ministry of Emergency Management & Ministry of Education, Beijing Normal University, Beijing 100875, China
4 Beijing Normal University State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing 100875, China

Received:2021-12-02 Revised:2022-03-07 Online:2022-11-30 Published:2022-10-27

摘要/Abstract

摘要：

中国城镇和乡村住房建筑地震设防水平差距较大，暴露在低设防农村与高密集城镇下的人口因此面临较高的地震风险，面向地震设防风险分析未来城乡人口及暴露特征具有重要意义。本文基于地震烈度区划图和人口-发展-环境（PDE）模型，模拟分析了5种共享社会经济路径（SSPs）情景下的未来城乡人口地震灾害时空暴露。结果表明：(1)除SSP3下城镇人口数量持续增加外，其他SSP情景下各地区城镇人口数量均先增后降，农村人口数量受城镇化影响呈持续下降趋势；(2)城镇与农村地震灾害高、较高人口暴露等级空间分布相似，集中在华北、西南与东部沿海地区；(3)相较于有设防的城镇地区，无设防农村地震人口暴露等级偏高，高暴露、较高暴露等级的数量偏多，未来城镇人口暴露等级有所上升，而农村人口暴露等级逐渐降低。

关键词: 人口暴露, 城乡差异, 设防水平, 地震灾害, 共享社会经济路径（SSP）, 气候变化

Abstract:

There is a huge gap between the seismic fortification level of urban and rural housing buildings in China. The population exposed to low fortification rural areas and high-density cities are faced with high seismic risk. Therefore, it is of great significance to analyse the future urban and rural population and their exposure characteristics. Based on the data of the sixth national population census, this paper uses seismic intensity distribution and the population development environment (PDE) model to simulate the urban and rural population exposure to earthquake disaster of China’s city level units from 2010 to 2100 under five shared socio-economic scenarios (SSPs). The results show that: (1) Except for the continuous increase of urban population under SSP3, other SSP paths’ number of urban population in various regions increased first and then decreased, and rural population is declining due to urbanization; (2) The spatial distribution of high and medium high population exposure levels in urban and rural areas is similar, concentrated in North China, southwestern and eastern coastal areas of China; (3) Compared with fortified urban areas, the exposure level of non-fortified rural areas is high, and the number of high exposure areas are large. In the future, the exposure level of urban population will rise, while the exposure level of rural population will gradually decrease.

Key words: Population exposure, Urban and rural differences, Fortification level, Earthquake disaster, Shared Socioeconomic Pathway (SSP), Climate change

张化, 李汶莉, 李雪敏, 董琳, 杨有田, 张国明, 许映军. 面向地震设防风险的未来中国城乡人口情景及暴露特征[J]. 气候变化研究进展, 2022, 18(6): 707-719.

ZHANG Hua, LI Wen-Li, LI Xue-Min, DONG Lin, YANG You-Tian, ZHANG Guo-Ming, XU Ying-Jun. Analysis of urban and rural population scenarios and exposure characteristics in China in the future for the prevention of earthquake risk[J]. Climate Change Research, 2022, 18(6): 707-719.

图/表 11

图1 未来人口模拟技术路线示意图

Fig. 1 Schematic diagram of future population simulation technical route

表1 中国总体城市化率目标设置

Table 1 Target setting of China’s urbanization rate

表2 2010—2100年中国不同等级生育率

Table 2 Fertility rate at different levels in China from 2010 to 2100

图2 第五代中国地震动峰值加速度（PGA）区划图注：g表示重力加速度，1g≈9.81 m/s2，0.1g代表的地震动峰值加速度则为0.981 m/s2。图来源于中国地震局。

Fig. 2 Seismic ground motion parameters zonation map (PGA) of China (China Earthquake Administration)

图3 PGA等级与城乡人口暴露等级对照图

Fig. 3 Classification of exposure levels of urban and rural population to PGA

图4 SSP情景下中国城镇和农村未来人口数量变化

Fig. 4 Future population change in urban and rural China under SSP scenario

图5 2015年城乡人口模拟结果误差分析注：柱状图的顶部为误差线，误差线长度越长，模拟结果一致性越低。图中大部分地市误差线较短，一致性较高。

Fig. 5 Error analysis of urban and rural population simulation results in 2015

图6 SSP1、SSP3、SSP5情景下中国城镇未来人口数量空间分布图

Fig. 6 Spatial distribution of future urban population in China under SSP1, SSP3 and SSP5

图7 SSP1、SSP3、SSP5情景下中国农村未来人口空间分布图

Fig. 7 Spatial distribution of future rural population in China under SSP1, SSP3 and SSP5

图8 SSP1、SSP3、SSP5情景下中国城镇未来人口地震灾害风险暴露等级

Fig. 8 Earthquake disasters exposure level of future urban population in China under SSP1, SSP3 and SSP5

图9 SSP1、SSP3、SSP5情景下中国农村未来人口地震灾害风险暴露等级

Fig. 9 Earthquake disasters exposure level of future rural population in China under SSP1, SSP3 and SSP5

参考文献 34

[1]	张培震, 邓起东, 张竹琪, 等. 中国大陆的活动断裂、地震灾害及其动力过程[J]. 中国科学:地球科学, 2013, 43 (10): 1607-1620.
	Zhang P Z, Deng Q D, Zhang Z Q, et al. Active faults, earthquake disasters and their dynamic processes in Chinese mainland[J]. Scientia Sinica: Terrae, 2013, 43 (10): 1607-1620 (in Chinese) doi: 10.1360/zd-2013-43-10-1607 URL
[2]	刘培玄, 王伟. 我国农村典型民居抗震设防问题分析与建议[J]. 中国减灾, 2019 (21): 16-19.
	Liu P X, Wang W. Analysis and suggestions on seismic fortification of typical rural houses in China[J]. Disaster Reduction in China, 2019 (21): 16-19 (in Chinese)
[3]	金晓霞. 不设防农村与高风险城市之痛[J]. 中国减灾, 2011 (7): 12-14.
	Jin X X. Defects of unprotected rural areas and high-risk cities[J]. Disaster Reduction in China, 2011 (7): 12-14 (in Chinese)
[4]	张津. 甘肃农村地震成灾机制及防震减灾研究[D]. 中国地震局兰州地震研究所, 2014.
	Zhang J. Research on earthquake disaster formation mechanism and disaster reduction in rural area of Gansu province[D]. Lanzhou Institute of Seismology, 2014 (in Chinese)
[5]	叶耀先. 农村建设抗震[J]. 建筑技术与设计, 2008 (7): 84-93.
	Ye Y X. Earthquake resistance of rural construction[J]. Architecture Technology & Design, 2008 (7): 84-93 (in Chinese)
[6]	周福霖. 隔震、消能减震与结构控制体系: 终止我国城乡地震灾难的必然技术选择[J]. 城市与减灾, 2016 (5): 1-10.
	Zhou F L. Seismic isolation, energy dissipation and structural control system: the inevitable technical choice to end the urban and rural earthquake disaster in China[J]. Urban and Disaster Reduction, 2016 (5): 1-10 (in Chinese)
[7]	国务院办公厅. 《国家综合防灾减灾规划(2016—2020年)》[EB/OL]. 2017 [2022-06-15]. http://www.gov.cn/zhengce/content/2017-01/13/content_5159459.htm.
	General Office of The State Council. National comprehensive plan of disaster prevention and mitigation (2016-2020)[EB/OL]. 2017 [2022-06-15]. http://www.gov.cn/zhengce/content/2017-01/13/content_5159459.htm (in Chinese)
[8]	吴绍洪, 赵东升. 中国气候变化影响、风险与适应研究新进展[J]. 中国人口·资源与环境, 2020, 30 (6): 1-9.
	Wu S H, Zhao D S. Progress on the impact, risk and adaptation of climate change in China[J]. China Population, Resources and Environment, 2020, 30 (6): 1-9 (in Chinese)
[9]	van Vuuren D P, Riahi K, Moss R, et al. A proposal for a new scenario framework to support research and assessment in different climate research communities[J]. Global Environmental Change, 2012, 22 (1): 21-35 doi: 10.1016/j.gloenvcha.2011.08.002 URL
[10]	van Vuuren D P, Kriegler E, O’Neill B C, et al. A new scenario framework for climate change research: scenario matrix architecture[J]. Climatic Change, 2014, 122: 373-386 doi: 10.1007/s10584-013-0906-1 URL
[11]	姜彤, 赵晶, 景丞, 等. IPCC共享社会经济路径下中国和分省人口变化预估[J]. 气候变化研究进展, 2017, 13 (2): 128-137.
	Jang T, Zhao J, Jing C, et al. National and provincial population projected to 2100 under the shared socioeconomic pathways in China[J]. Climate Change Research, 2017, 13 (2): 128-137 (in Chinese)
[12]	Huang J, Qin D, Jiang T, et al. Effect of fertility policy changes on the population structure and economy of China: from the perspective of the shared socioeconomic pathways[J]. Earth’s Future, 2019, 7: 250-265 doi: 10.1029/2018EF000964 URL
[13]	Chen Y, Guo F, Wang J, et al. Provincial and gridded population projection for China under shared socioeconomic pathways from 2010 to 2100[J]. Scientific Data, 2020, 7: 255-262 doi: 10.1038/s41597-020-00597-w URL
[14]	姜彤, 王艳君, 袁佳双, 等. “一带一路”沿线国家2020—2060年人口经济发展情景预测[J]. 气候变化研究进展, 2018, 14 (2): 155-164.
	Jang T, Wang Y J, Yuan J S, et al. Projection of population and economy in the Belt and Road countries (2020-2060)[J]. Climate Change Research, 2018, 14 (2): 155-164 (in Chinese)
[15]	Lutz W, KC S. Global human capital: integrating education and population[J]. Science, 2011, 333 (6042): 587-592 doi: 10.1126/science.1206964 pmid: 21798940
[16]	KC S, Lutz W. The human core of the shared socioeconomic pathways: population scenarios by age, sex and level of education for all countries to 2100[J]. Global Environmental Change, 2014, 42 (1): 181-189 doi: 10.1016/j.gloenvcha.2014.06.004 URL
[17]	郑晓瑛, 陈功, 庞丽华, 等. 中国人口、人力资本变化趋势[J]. 市场与人口分析, 2007 (1): 3-13.
	Zheng X Y, Chen G, Pang L H, et al. Future population and human capital in China[J]. Population and Development, 2007 (1): 3-13 (in Chinese)
[18]	Zhang J, Gao P, Fang F. An ATPSO-BP neural network modelling and its application in mechanical property prediction[J]. Computational Materials Science, 2019, 163: 262-266 doi: 10.1016/j.commatsci.2019.03.037 URL
[19]	曹桂英, 任强. 未来全国和不同区域人口城镇化水平预测[J]. 人口与经济, 2005 (4): 51-56, 67.
	Cao G Y, Ren Q. The national and regional urbanization projection for China[J]. Population & Economics, 2005 (4): 51-56, 67 (in Chinese)
[20]	Shang H L, Smith P W F, Bijak J, et al. A multilevel functional data method for forecasting population, with an application to the United Kingdom[J]. International Journal of Forecasting, 2019, 32 (3): 629-649 doi: 10.1016/j.ijforecast.2015.10.002 URL
[21]	王豫燕, 王艳君, 姜彤. 江苏省暴雨洪涝灾害的暴露度和脆弱性时空演变特征[J]. 长江科学院院报, 2016, 33 (4): 27-32.
	Wang Y Y, Wang Y J, Jang T. Spatial-temporal characteristics of exposure and vulnerability to flood disaster in Jiangsu province[J]. Journal of Yangtze River Scientific Research Institute, 2016, 33 (4): 27-32 (in Chinese)
[22]	李柔珂, 李耀辉, 徐影. 未来中国地区的暴雨洪涝灾害风险预估[J]. 干旱气象, 2018, 36 (3): 341-352.
	Li R K, Li Y H, Xu Y. Projection of rainstorm and flooding disaster risk in China in the 21st century[J]. Journal of Arid Meteorology, 2018, 36 (3): 341-352 (in Chinese)
[23]	Liao X L, Xu W, Zhang J L, et al. Global exposure to rainstorms and the contribution rates of climate change and population change[J]. Science of The Total Environment, 2019 (663): 644-653
[24]	杨佩国, 靳京, 赵东升, 等. 基于历史暴雨洪涝灾情数据的城市脆弱性定量研究:以北京市为例[J]. 地理科学, 2016, 36 (5): 733-741. doi: 10.13249/j.cnki.sgs.2016.05.011
	Yang P G, Jin J, Zhao D S, et al. An urban vulnerability study based on historical flood data: a case study of Beijing[J]. Scientia Geographica Sinica, 2016, 36 (5): 733-741 (in Chinese) doi: 10.13249/j.cnki.sgs.2016.05.011
[25]	韩钦梅, 吕建军, 史培军. 湖北省暴雨人口暴露时空特征与贡献率研究[J]. 灾害学, 2018, 33 (4): 191-196.
	Han Q M, Lyu J J, Shi P J. Spatial temporal characteristics and contribution rate of rainstorm population exposure in Hubei[J]. Journal of Catastrophology, 2018, 33 (4): 191-196 (in Chinese)
[26]	井源源, 方建, 史培军. 未来气候变化情景下湖北省极端降水的人口暴露分析[J]. 北京师范大学学报: 自然科学版, 2020, 56 (5): 700-709.
	Jing Y Y, Fang J, Shi P J. Analysis of population exposure to extreme precipitation in Hubei province under the climate change scenarios[J]. Journal of Beijing Normal University: Natural Science, 2020, 56 (5): 700-709 (in Chinese)
[27]	王军, 王广州. 中国育龄人群的生育意愿及其影响估计[J]. 中国人口科学, 2013, 4: 26-35.
	Wang J, Wang G Z. Reproductive population’s fertility desire and its influence in China[J]. Chinese Journal of Population Science, 2013, 4: 26-35 (in Chinese)
[28]	庄亚儿, 姜玉, 王志理, 等. 当前我国城乡居民的生育意愿: 基于2013年全国生育意愿调查[J]. 人口研究, 2014, 38 (3): 3-13.
	Zhuang Y E, Jang Y, Wang Z L, et al. Fertility intention of rural and urban residents in China: results from the 2013 national fertility intention survey[J]. Population Research, 2014, 38 (3): 3-13 (in Chinese)
[29]	中华人民共和国住房和城乡建设部. GB55002—2021建筑与市政工程抗震通用规范[S]. 北京: 中国建筑出版传媒有限公司, 2021.
	Ministry of Housing and Urban-Rural Development of People’s Republic of China. GB55002—2021 general standard for earthquake resistance of building and municipal engineering[S]. Beijing: China Architecture Publication Medium Limited Company, 2021 (in Chinese)
[30]	Ni H H, Chen A, Chen N. Some extensions on risk matrix approach[J]. Safety Science, 2010, 48: 1269 doi: 10.1016/j.ssci.2010.04.005 URL
[31]	Eskesen S D, Tengborg P, KampmannJ, et al. Guidelines for tunnelling risk management: international tunnelling association, working group No.2[J]. Tunnelling and Underground Space Technology, 2004, 19 (3): 217-237 doi: 10.1016/j.tust.2004.01.001 URL
[32]	孙柏涛. 中国编第五代地震区划图超九成农村房屋无抗震措施[EB/OL]. 2011 [2021-11-22]. http://cn.chinagate.cn/povertyrelief/2011-11/14/content_23906357.htm.
	Sun B T. The fifth seismic ground motion parameters zonation map compiled more than 90% of rural houses have no seismic measures[EB/OL]. 2011 [2021-11-22]. http://cn.chinagate.cn/povertyrelief/2011-11/14/content_23906357.htm (in Chinese)
[33]	曹丽格, 方玉, 姜彤, 等. IPCC影响评估中的社会经济新情景(SSPs)进展[J]. 气候变化研究进展, 2012, 8 (1): 74-78.
	Cao L G, Fang Y, Jiang T, et al. Advances in shared socio-economic pathways for climate change research and assessment[J]. Climate Change Research, 2012, 8 (1): 74-78 (in Chinese)
[34]	翁宇威, 蔡闻佳, 王灿. 共享社会经济路径(SSPs)的应用与展望[J]. 气候变化研究进展, 2020, 16 (2): 215-222.
	Weng Y W, Cai W J, Wang C. The application and future directions of the shared socioeconomic pathways (SSPs)[J]. Climate Change Research, 2020, 16 (2): 215-222 (in Chinese)

面向地震设防风险的未来中国城乡人口情景及暴露特征

Analysis of urban and rural population scenarios and exposure characteristics in China in the future for the prevention of earthquake risk

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 34

相关文章 15

编辑推荐

Metrics

本文评价

[1]	王玉洁, 林欣. 京津冀城市群气候变化及影响适应研究综述[J]. 气候变化研究进展, 2022, 18(6): 743-755.
[2]	高美勋, 陈敏鹏, 滕飞. “一带一路”沿线国家适应气候变化的技术需求评估[J]. 气候变化研究进展, 2022, 18(6): 731-742.
[3]	梅梅, 侯威, 周星妍. 新、旧气候态差异及对中国地区气候和极端事件评估业务的影响[J]. 气候变化研究进展, 2022, 18(6): 653-669.
[4]	张熹, 陈敏鹏. 适应与绿色复苏：应对新冠疫情和气候复合风险的协同[J]. 气候变化研究进展, 2022, 18(6): 720-730.
[5]	蒋含颖, 高翔, 王灿. 气候变化国际合作的进展与评价[J]. 气候变化研究进展, 2022, 18(5): 591-604.
[6]	白泉, 胡姗, 谷立静. 对IPCC AR6报告建筑章节的介绍和解读[J]. 气候变化研究进展, 2022, 18(5): 557-566.
[7]	王卓妮, 袁佳双, 庞博, 黄磊. IPCC AR6 WGIII报告减缓主要结论、亮点和启示[J]. 气候变化研究进展, 2022, 18(5): 531-537.
[8]	马丽娟, 效存德, 康世昌. 全球主要山地气候变化特征和异同——IPCC AR6 WGI报告和SROCC综合解读[J]. 气候变化研究进展, 2022, 18(5): 605-621.
[9]	刘俊国, 孟莹, 张学静. IPCC AR6报告解读：地下水[J]. 气候变化研究进展, 2022, 18(4): 414-421.
[10]	段居琦, 袁佳双, 徐新武, 居辉. 对IPCC AR6报告中有关农业系统结论的解读[J]. 气候变化研究进展, 2022, 18(4): 422-432.
[11]	张百超, 庞博, 秦云, 韩振宇, 陆波. IPCC AR6报告关于气候恢复力发展的解读[J]. 气候变化研究进展, 2022, 18(4): 460-467.
[12]	王蕾, 张百超, 石英, 韩振宇, 陆波. IPCC AR6报告关于气候变化影响和风险主要结论的解读[J]. 气候变化研究进展, 2022, 18(4): 389-394.
[13]	秦云, 徐新武, 王蕾, 韩振宇, 陆波. IPCC AR6报告关于气候变化适应措施的解读[J]. 气候变化研究进展, 2022, 18(4): 452-459.
[14]	汪军能, 秦年秀, 姜彤, 苏布达. IPCC AR6报告解读：气候变化对城市、住区和关键基础设施的影响与适应[J]. 气候变化研究进展, 2022, 18(4): 433-441.
[15]	黄存瑞, 刘起勇. IPCC AR6报告解读：气候变化与人类健康[J]. 气候变化研究进展, 2022, 18(4): 442-451.